Tag
#MIT Schwarzman College of Computing
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In game theory, generalists sometimes win out over specialists
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Could AI tell you where you left your keys?
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When it comes to predicting people’s preferences, it pays to consider “the power of three”
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MIT affiliates win 2026 Hertz Foundation Fellowships
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NSF renews support for MIT-led AI and physics institute, expanding a new model for discovery
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Teaching AI agents to ask better questions by playing “Battleship”
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MIT researchers teach AI models to interpret charts
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Building AI models that understand chemical principles
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Justin Solomon appointed associate dean of engineering education
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Games people — and machines — play: Untangling strategic reasoning to advance AI
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Solving the “Whac-a-mole dilemma”: A smarter way to debias AI vision models
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The MIT-IBM Computing Research Lab launches to shape the future of AI and quantum computing
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Enabling privacy-preserving AI training on everyday devices
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A faster way to estimate AI power consumption
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MIT scientists build the world’s largest collection of Olympiad-level math problems, and open it to everyone
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Teaching AI models to say “I’m not sure”
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Jacob Andreas and Brett McGuire named Edgerton Award winners
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Human-machine teaming dives underwater
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New technique makes AI models leaner and faster while they’re still learning
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Helping data centers deliver higher performance with less hardware
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Evaluating the ethics of autonomous systems
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Preview tool helps makers visualize 3D-printed objects
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AI system learns to keep warehouse robot traffic running smoothly
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Augmenting citizen science with computer vision for fish monitoring
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MIT and Hasso Plattner Institute establish collaborative hub for AI and creativity
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A better method for identifying overconfident large language models
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Generative AI improves a wireless vision system that sees through obstructions
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MIT-IBM Watson AI Lab seed to signal: Amplifying early-career faculty impact
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Can AI help predict which heart-failure patients will worsen within a year?
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3 Questions: On the future of AI and the mathematical and physical sciences
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A better method for planning complex visual tasks
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Improving AI models’ ability to explain their predictions
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A “ChatGPT for spreadsheets” helps solve difficult engineering challenges faster
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New method could increase LLM training efficiency
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Mixing generative AI with physics to create personal items that work in the real world
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AI to help researchers see the bigger picture in cell biology
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Parking-aware navigation system could prevent frustration and emissions
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Personalization features can make LLMs more agreeable
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Study: Platforms that rank the latest LLMs can be unreliable
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Helping AI agents search to get the best results out of large language models
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Antonio Torralba, three MIT alumni named 2025 ACM fellows
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Katie Spivakovsky wins 2026 Churchill Scholarship
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Why it’s critical to move beyond overly aggregated machine-learning metrics
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At MIT, a continued commitment to understanding intelligence
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Generative AI tool helps 3D print personal items that sustain daily use
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3 Questions: How AI could optimize the power grid
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MIT scientists investigate memorization risk in the age of clinical AI
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Guided learning lets “untrainable” neural networks realize their potential
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A new way to increase the capabilities of large language models
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3 Questions: Using computation to study the world’s best single-celled chemists
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Enabling small language models to solve complex reasoning tasks
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New MIT program to train military leaders for the AI age
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New method improves the reliability of statistical estimations
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New materials could boost the energy efficiency of microelectronics
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MIT researchers “speak objects into existence” using AI and robotics
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A smarter way for large language models to think about hard problems
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MIT engineers design an aerial microrobot that can fly as fast as a bumblebee
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New control system teaches soft robots the art of staying safe
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Researchers discover a shortcoming that makes LLMs less reliable
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MIT scientists debut a generative AI model that could create molecules addressing hard-to-treat diseases
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Understanding the nuances of human-like intelligence
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Charting the future of AI, from safer answers to faster thinking
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MIT researchers propose a new model for legible, modular software
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Teaching robots to map large environments
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3 Questions: How AI is helping us monitor and support vulnerable ecosystems
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A faster problem-solving tool that guarantees feasibility
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Five with MIT ties elected to National Academy of Medicine for 2025
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Creating AI that matters
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New software designs eco-friendly clothing that can reassemble into new items
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Method teaches generative AI models to locate personalized objects
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MIT Schwarzman College of Computing and MBZUAI launch international collaboration to shape the future of AI
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Using generative AI to diversify virtual training grounds for robots
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Fighting for the health of the planet with AI
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New prediction model could improve the reliability of fusion power plants
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AI maps how a new antibiotic targets gut bacteria
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Responding to the climate impact of generative AI
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New AI system could accelerate clinical research
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How to build AI scaling laws for efficient LLM training and budget maximization
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Machine-learning tool gives doctors a more detailed 3D picture of fetal health
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DoE selects MIT to establish a Center for the Exascale Simulation of Coupled High-Enthalpy Fluid–Solid Interactions
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A greener way to 3D print stronger stuff
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A new generative AI approach to predicting chemical reactions
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3 Questions: The pros and cons of synthetic data in AI
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3 Questions: On biology and medicine’s “data revolution”
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MIT researchers develop AI tool to improve flu vaccine strain selection
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Simpler models can outperform deep learning at climate prediction
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A new way to test how well AI systems classify text